Data Management

Multi-Level Dimensionality Reduction Methods Using Feature Selection and Feature Extraction

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Executive Summary

This paper presents a novel feature selection method called Feature Quality (FQ) measure based on the quality measure of individual features. The authors also propose novel combinations of two level and multi level dimensionality reduction methods which are based on the feature selection like mutual correlation, FQ measure and feature extraction methods like PCA(Principal Component Analysis)/LPP(Locality Preserving Projection). These multi level dimensionality reduction methods integrate feature selection and feature extraction methods to improve the classification performance.

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